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Artificial Intelligence Architect

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Onsite

Artificial Intelligence Architect

Aptara

Artificial Intelligence Architect

Skills

Google Cloud PlatformDockerNodeDjangoPythonData ScienceE-LearningMicroservicesPostgreSQLAIAWSGitHubKubernetesCRMFastAPIAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Pune, Maharashtra, India

Work mode:

Onsite

Published on:

17 August 2026

What they need


AI Architect

Experience: 10+ years in web application development/DevOps, with 5+ years in AI system design and cloud-native architecture.

Job Purpose:
Design and lead scalable AI solutions that optimize eLearning development, automate content creation, improve productivity, and enhance learning experiences through Generative AI and automation.

Key Responsibilities:

  • Lead AI strategy and design end-to-end AI architecture for eLearning and enterprise solutions.
  • Design and implement LLM, RAG, and Agentic AI solutions using frameworks such as LangChain or Semantic Kernel.
  • Architect AI-powered text, audio, video, and image generation capabilities.
  • Design secure and scalable cloud architectures on AWS, Azure, or GCP.
  • Define data architecture, governance, security, and Responsible AI practices.
  • Drive MLOps/DevOps, including CI/CD, Docker, Kubernetes, monitoring, and model lifecycle management.
  • Integrate AI solutions with LMS/LXP, CMS, CRM, SCORM, xAPI, and LTI platforms through APIs and microservices.
  • Establish coding/API standards and conduct architecture and code reviews.
  • Collaborate with AI, engineering, product, and business teams to deliver enterprise-grade solutions.

Key Skills:

  • AI/GenAI: OpenAI/Claude, LLMs, Prompt Engineering, RAG, Agentic AI, LangChain/Semantic Kernel, Embeddings, Vector Databases.
  • Backend: Python (FastAPI/Django) or Node.js, REST APIs, WebSockets, session/state management.
  • Cloud: AWS/Azure/GCP with hands-on experience in secure, scalable deployments.
  • DevOps: Docker, Kubernetes, CI/CD, GitHub Actions or equivalent.
  • Database: PostgreSQL or equivalent + Vector DB such as Pinecone, Weaviate, or pgvector.
  • Security: IAM, secrets management, encryption, data privacy, and secure AI architecture.

Qualification:

  • Bachelors/Master’s in Computer Science, Engineering, Data Science, or equivalent experience.
  • 5+ years of experience in AI system design.
  • Hands-on experience with LLMs, RAG, Vector Databases, and API-based AI integration.
  • Strong understanding of cloud-native, secure, and scalable AI architectures.

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